1286. Taniborbactam Inhibits Cefepime-Hydrolyzing Variants of Pseudomonas-derived Cephalosporinase (PDC)

Background PDC is a class C β-lactamase in P. aeruginosa. PDC-88 is a variant characterized by a Thr-Pro amino acid deletion in the R2-loop (Δ289-290; Fig. 1). This deletion reduces susceptibility to cefepime (FEP), ceftazidime (CAZ), and ceftolozane-tazobactam (TOL/TZB), but the mechanism for this “gain of function” is unknown. Taniborbactam (TAN) is a novel cyclic boronate β-lactamase inhibitor (BLI) with activity against all four β-lactamase classes and is currently undergoing a phase 3 clinical trial paired with FEP. Herein, we studied the extended-spectrum AmpC (ESAC) phenotype of PDC-88 and examined the ability of TAN to inhibit this variant. Structure of PDC-1 (PDB ID: 4GZB) with PDC-88 deleted residues in red and substitutions in green. All four amino acid substitutions (T79A, V178L, V329I, and G346A) are common (occurring in 10% or more of PDC variants) and have not been associated with resistance. Image rendered using UCSF Chimera. Methods Broth microdilution minimum inhibitory concentrations (MIC) were determined in accordance with CLSI. PDC-3 and PDC-88 were purified, and steady-state enzyme kinetics were determined. Quadrupole time-of-flight mass spectrometry (Q-TOF-MS) was performed. Results In isogenic E. coli expressing PDC-3 or PDC-88, FEP MIC increased 8- or 128-fold, respectively, compared to the empty vector. Addition of TAN at 4 μg/ml restored FEP activity with MIC lowered to 0.25 μg/ml (Table 1) for both PDC-3 and PDC-88 bearing strains. PDC-88 demonstrated a 9-fold lower KM, 3.4-fold lower kcat, and 2.6-fold higher kcat/KM for FEP compared to PDC-3 (Table 2A). TAN Ki values were 4- to 10-fold lower than avibactam (AVI) and 40- to 95-fold lower than TZB. The TAN acylation constant (k2/K) was 7- to 12-fold greater than AVI and 133- to 366-fold higher than TZB (Table 2B). Q-TOF-MS revealed faster deacylation of FEP by PDC-88 compared to TOL and CAZ. TOL was acylated and deacylated by PDC-88 but not by PDC-3. CAZ was readily acylated but slowly deacylated by PDC-88 compared to PDC-3 (Fig. 2). Cefepime Minimum Inhibitory Concentration (MIC) for PDC-1 and a series of partial R2-loop deletions with and without taniborbactam, avibactam, and tazobactam. In all variants, taniborbactam and avibactam restored susceptiblity while tazobactam is less effective against PDC-88 and variants. Summary of kinetic constants. (A) Comparison of Michaelis constant (KM), turnover number (kcat), and catalytic efficiency (kcat/KM) of nitrocefin and cefepime with PDC-3 and PDC-88. (B) Comparison of inhibition constant (Ki) and acylation constant (k2/K) for avibactam, tazobactam, and taniborbactam with PDC-3 and PDC-88. Graphical summary of mass spectrometry results for substrate acyl-enzyme complex capture experiments. FEP, cefepime; CAZ, ceftazidime; TOL, ceftolozane. Primes indicate a modified substrate (loss of R2 group). TOL does not form an acyl-enzyme complex with PDC-3. Conclusion Different kinetic constants are responsible for the elevated cephalosporin MICs. We posit that PDC-88 increases FEP MIC by enhanced hydrolysis; TOL MICs by enabling acylation; and CAZ MICs by both trapping and enhanced hydrolysis. TAN inhibits both PDC-3 and PDC-88 with similar kinetic profiles. Notably, TAN appears to be a more efficient inhibitor of PDC than current BLIs targeted for use against P. aeruginosa (lower Ki, higher k2/K values). The combination of TAN and FEP may represent an important treatment option for P. aeruginosa isolates that develop ESAC phenotypes. Disclosures Focco van den Akker, PhD, Venatorx Pharmaceuticals, Inc. (Grant/Research Support) Brittany A. Miller, BS, Venatorx Pharmaceuticals, Inc. (Employee) Tsuyoshi Uehara, PhD, Venatorx Pharmaceuticals, Inc. (Employee) David A. Six, PhD, Venatorx Pharmaceuticals, Inc. (Employee) Krisztina M. Papp-Wallace, Ph.D., Merck & Co., Inc. (Grant/Research Support)Spero Therapeutics, Inc. (Grant/Research Support)Venatorx Pharmaceuticals, Inc. (Grant/Research Support)Wockhardt Ltd. (Other Financial or Material Support, Research Collaborator) Robert A. Bonomo, MD, entasis (Research Grant or Support)Merck (Grant/Research Support)NIH (Grant/Research Support)VA Merit Award (Grant/Research Support)VenatoRx (Grant/Research Support)

Southern Ocean Food Web Modelling: Progress, Prognoses, and Future Priorities for Research and Policy Makers

Graphical AbstractGraphical summary of multiple aspects of Southern Ocean food web structure and function including alternative energy pathways through pelagic food webs, climate change and fisheries impacts and the importance of microbial networks and benthic systems.

Liver Impairment—The Potential Application of Volatile Organic Compounds in Hepatology

Liver diseases are currently diagnosed through liver biopsy. Its invasiveness, costs, and relatively low diagnostic accuracy require new techniques to be sought. Analysis of volatile organic compounds (VOCs) in human bio-matrices has received a lot of attention. It is known that a musty odour characterises liver impairment, resulting in the elucidation of volatile chemicals in the breath and other body fluids such as urine and stool, which may serve as biomarkers of a disease. Aims: This study aims to review all the studies found in the literature regarding VOCs in liver diseases, and to summarise all the identified compounds that could be used as diagnostic or prognostic biomarkers. The literature search was conducted on ScienceDirect and PubMed, and each eligible publication was qualitatively assessed by two independent evaluators using the SANRA critical appraisal tool. Results: In the search, 58 publications were found, and 28 were kept for inclusion: 23 were about VOCs in the breath, one in the bile, three in urine, and one in faeces. Each publication was graded from zero to ten. A graphical summary of the metabolic pathways showcasing the known liver disease-related VOCs and suggestions on how VOC analysis on liver impairment could be applied in clinical practice are given.

Timelines as a Tool for Learning about Space Weather Storms

Space weather storms typically have solar, interplanetary, geophysical and societal-effect components that overlap in time, making it hard for students and novices to determine cause-and-effect relationships and relative timing. To address this issue, we use timelines to provide context for space weather storms of different intensities. First, we present a timeline and tabular description for the great auroral storms of the last 500 years as an example for space climate. The graphical summary for these 14 events suggests that they occur about every 40-60 years, although the distribution of such events is far from even. One outstanding event in 1770 may qualify as a one-in-500-year auroral event, based on duration. Additionally, we present two examples that describe space weather storms using solar, geospace and effects categories. The first of these is for the prolonged storm sequence of late January1938 that produced low-latitude auroras and space weather impacts on mature technology (telegraphs) and on high frequency radio communication for aviation, which was a developing technology. To illustrate storm effects in the space-age, we produce a detailed timeline for the strong December 2006 geomagnetic storm that impacted numerous space-based technologies for monitoring space weather and for communication and navigation. During this event there were numerous navigations system disturbances and hardware disruptions. We adopt terminology developed in many previous space weather studies and blend it with historical accounts to create graphical timelines to help organize and disentangle the events presented herein.

CAMELS-FR: A large sample, hydroclimatic dataset for France, to support model testing and evaluation

<p>Over the last decades, the development of large sample hydrology has allowed a generalization of sound model evaluation and testing practices (Andréassian et al., 2006; Gupta et al. 2014), based on various types of split-sample tests. This presentation aims at illustrating some of these tests, while introducing at the same time a French dataset that we have been working with for many years. This dataset has been assembled at INRAE (HYCAR research unit), based on an automatized assembling of national data products (Delaigue et al. 2020). CAMELS-FR will provide daily hydro-meteorological time series (streamflow, solid and liquid precipitation, potential evapotranspiration, temperature, etc.) covering the 1958-2020 period. Catchment characteristics such as land cover, topography (i.e. elevation and slope distributions, drainage density, topographic index, etc.) will be provided, with information about possible regulations upstream, and with some a priori information on data quality. Graphical summary sheets for each catchment are already available.</p><p>This approach is part of the CAMELS international initiative (Addor et al., 2017), whose purpose is to facilitate reproducible hydrological research by the use of large sample catchment datasets, and the CAMELS-FR dataset will be made available to scientific users in partnership with data owners.</p><p><strong>References</strong></p><p>Addor, N., Newman, A. J., Mizukami, N., Clark, M. P. (2017). The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017</p><p>Andréassian, V., Hall, A., Chahinian, N., Schaake, J. (2006). Introduction and Synthesis: Why should hydrologists work on a large number of basin data sets? IAHS Publication, 307, 1-5, https://hal.inrae.fr/hal-02588687.</p><p>Delaigue, O., Génot, B., Lebecherel, L., Brigode, P., Bourgin, P.Y. (2020). Database of watershed-scale hydroclimatic observations in France. Université Paris-Saclay, INRAE, HYCAR Research Unit, Hydrology group, Antony, https://webgr.inrae.fr/base-de-donnees.</p><p>Gupta, H.V., Perrin, C., Blöschl, G., Montanari, A., Kumar, R., Clark, M., Andréassian, V. (2014). Large-sample hydrology: A need to balance depth with breadth. Hydrology and Earth System Sciences, 18(2), 463–477, doi: https://doi.org/10.5194/hess-18-463-2014.</p>

What is the optimum design for my animal experiment?

Within preclinical research, attention has focused on experimental design and how current practices can lead to poor reproducibility. There are numerous decision points when designing experiments. Ethically, when working with animals we need to conduct a harm–benefit analysis to ensure the animal use is justified for the scientific gain. Experiments should be robust, not use more or fewer animals than necessary, and truly add to the knowledge base of science. Using case studies to explore these decision points, we consider how individual experiments can be designed in several different ways. We use the Experimental Design Assistant (EDA) graphical summary of each experiment to visualise the design differences and then consider the strengths and weaknesses of each design. Through this format, we explore key and topical experimental design issues such as pseudo-replication, blocking, covariates, sex bias, inference space, standardisation fallacy and factorial designs. There are numerous articles discussing these critical issues in the literature, but here we bring together these topics and explore them using real-world examples allowing the implications of the choice of design to be considered. Fundamentally, there is no perfect experiment; choices must be made which will have an impact on the conclusions that can be drawn. We need to understand the limitations of an experiment’s design and when we report the experiments, we need to share the caveats that inherently exist.

Propylene Yield from Olefin Plant Utilizing Box-Cox Transformation in Regression Analysis

Propylene yield is one of the key operating parameters that is monitored daily in the running olefin plant. This study was conducted in the actual world-scale olefin plant to measure the impact of identified controlled variables on the propylene yield. The Box-Cox data transformation was adopted in the Regression Analysis using Minitab Software Version 18 due to non-normal data were observed after normality and stability test were conducted using Box Plot, I-MR Chart, Run Chart, Graphical Summary, and Normality Plot tools. The model concluded that propylene yield in the studied plant was contributed by the factors of -0.000243 Hearth Burner Flow, 0.01332 Integral Burner Flow, and 0.08598 Naphtha Feed Flow. The Response Optimizer tool also suggested that the propylene yield from naphtha liquid feed can be maximized at 11.22% with the control setting at 10,993.86 kg/hr of Hearth Burner Flow, 604.61 kg/hr of Integral Burner Flow, and 63.50 t/hr of Naphtha Feed Flow.

COVATOR: A Software for Chimeric Coronavirus Identification

The term chimeric virus was not popular in the last decades. Recently, according to current sequencing efforts in discovering COVID-19 Secrets, the generated information assumed the presence of 6 Coronavirus main strains, but coronavirus diverges into hundreds of sub-strains. the bottleneck is the mutation rate. With two mutation/month, humanity will meet a new sub-strain every month. Tracking new sequenced viruses is urgently needed because of the pathogenic effect of the new substrains. here we introduce COVATOR, A user-friendly and python-based software that identifies viral chimerism. COVATOR aligns input genome and protein that has no known source, against genomes and protein with known source, then gives the user a graphical summary.

A volumetric framework for quantum computer benchmarks

We propose a very large family of benchmarks for probing the performance of quantum computers. We call them volumetric benchmarks (VBs) because they generalize IBM's benchmark for measuring quantum volume \cite{Cross18}. The quantum volume benchmark defines a family of square circuits whose depth d and width w are the same. A volumetric benchmark defines a family of rectangular quantum circuits, for which d and w are uncoupled to allow the study of time/space performance trade-offs. Each VB defines a mapping from circuit shapes — (w,d) pairs — to test suites C(w,d). A test suite is an ensemble of test circuits that share a common structure. The test suite C for a given circuit shape may be a single circuit C, a specific list of circuits {C1…CN} that must all be run, or a large set of possible circuits equipped with a distribution Pr(C). The circuits in a given VB share a structure, which is limited only by designers' creativity. We list some known benchmarks, and other circuit families, that fit into the VB framework: several families of random circuits, periodic circuits, and algorithm-inspired circuits. The last ingredient defining a benchmark is a success criterion that defines when a processor is judged to have ``passed'' a given test circuit. We discuss several options. Benchmark data can be analyzed in many ways to extract many properties, but we propose a simple, universal graphical summary of results that illustrates the Pareto frontier of the d vs w trade-off for the processor being benchmarked.

Optogenetic activation of heterotrimeric Gi proteins by LOV2GIVe— a rationally engineered modular protein

ABSTRACTHeterotrimeric G-proteins are signal transducers that mediate the action of many natural extracellular stimuli as well as of many therapeutic agents. Non-invasive approaches to manipulate the activity of G-proteins with high precision are crucial to understand their regulation in space and time. Here, we engineered LOV2GIVe, a modular protein that allows the activation of Gi proteins with blue light. This optogenetic construct relies on a versatile design that differs from tools previously developed for similar purposes, i.e. metazoan opsins, which are light-activated GPCRs. To make LOV2GIVe, we fused a peptide derived from a non-GPCR protein that activates Gαi (but not Gαs, Gαq, or Gα12) to a small plant protein domain, such that light uncages the G-protein activating module. Targeting LOV2GIVe to cell membranes allowed for light-dependent activation of Gi proteins in different experimental systems. In summary, LOV2GIVe expands the armamentarium and versatility of tools available to manipulate heterotrimeric G-protein activity.GRAPHICAL SUMMARY